Last century, Lake Taihu (China) became serious eutrophic due to excessive nutrient input. During the 1980s, the first algal blooms emerged in the lake, reaching disastrous proportions in 2007. During that year, the intake of drinking water had to be shut down and millions of people had to look for an alternative source of drinking water. This raises the question whether such problems can be avoided. Of crucial importance in avoiding and reducing toxic algal blooms is the identification of the maximum nutrient load ecosystems can absorb, while remaining in a good ecological state. In this thesis, I aim to determine the critical nutrient load for Lake Taihu. I approach the search for critical nutrient loads of Lake Taihu in five steps with diversity as an overarching topic throughout this thesis: diversity in lakes, diversity in models, diversity in spatial distribution of nutrient and water sources, diversity in the development of lakes around the earth and finally diversity within specific lakes. From the long list of available models I chose the model PCLake to use in my analysis because it is the most extensively used food web model applied for bifurcation analysis of shallow aquatic ecosystems. The approach has resulted in a range of critical nutrient loads for different parts of Lake Taihu. Furthermore, critical nutrient loads depend on management goals, i.e. the maximum allowable chlorophyll-a concentration. According to the model results, total nutrient loads need to be more than halved to reach chlorophyll-a concentrations of 30-40 μg.L-1 in most sections of the lake. To prevent phytoplankton blooms with 20 μg.L-1 chlorophyll-a throughout Lake Taihu, both phosphorus and nitrogen loads need a nearly 90% reduction. This range contrasts to the single point of recovery that is often found for small shallow lakes. The range in critical nutrient loads found for Lake Taihu can be interpreted as providing a path of recovery for which each step leads to water quality improvement in certain parts of the lake. To reach total recovery, nutrient reduction seems to be the most promising management option.

The world is changing rapidly due to anthropogenic disturbance. Effects include: global warming, massive pollution, a changed global nitrogen cycle, high rates of land-use change, and exotic species spread. This has a tremendous impact on both natural and agricultural systems. To understand these impacts, good understanding of ecological systems and underlying drivers is necessary. Ecological systems can be studied at different levels of aggregation. Different levels of aggregation influence each other and are also influenced by external drivers like the environment. The population level is of particular interest, because many important ecological processes occur at the population level, like evolution, extinction, and invasion. Ecologists are increasingly recognizing that population processes are strongly influenced by one level of aggregation lower, the individual level. Individual heterogeneity (i.e. differences between individuals in performance), determines many population processes including population growth rate. However, the exact relations between individual heterogeneity, the external drivers of it, and the population level are not always well understood. Furthermore, methods to analyze these relations are not always available.

Individual heterogeneity occurs at different temporal scales, ranging from short- to long-term performance differences between individuals, where short- and long-term refer to the expected lifespan of the species in question. Short-term differences between individuals are relatively easily identifiable and are common in almost all species. But long-term differences are much harder to determine especially for long-lived organisms. Long-term differences between individuals in reproduction have been identified for several animal species, and in growth for several tree species, but less is known about the existence of such differences in other life forms (e.g. palms, lianas or clonal plants). Quantifying the extent to which individuals differ is essential for understanding the influence of individual heterogeneity on population processes. Super-performing individuals (i.e. individuals that persistently grow faster and reproduce more than others), probably contribute more to the growth of the population and therefore to future generations. Future populations will, therefore, have the genetic characteristics of the super-performers. Which characteristics this will be, depends on the genetic and environmental drivers of super-performance. Full understanding of the influence of individual heterogeneity on population processes, therefore, requires knowledge of the underlying causes of individual heterogeneity.

For many species, it is known that spatial variation in environmental conditions can cause short-term performance differences between individuals, but it is often not clear if the same environmental factors that cause short-term performance differences are also the environmental factors that cause long-term performance differences. Furthermore, genetic variation is known to cause performance differences, but to what extent is not well studied in natural long-lived plant populations. Within-population genetic variation can be maintained in habitats that are characterized by strong temporal or spatial heterogeneity in environmental conditions if the performance of a genotype relative to others depends on the environment it experiences.

Super-performing individuals possibly play an important role in the resistance and resilience of populations to disturbance (i.e. maintaining and recovering population growth rate under stress), because super-performers potentially contribute more to the recovery of the population. However, this depends on the relative tolerance to disturbance of super-performers compared to under-performers. A positive relation between performance and tolerance would make super-performers more important, while a negative relation would make them less important. Many types of disturbances entail leaf loss and tolerance to leaf loss is associated with performance being larger than what one would assume based on the amount of leaf area loss. Tolerance can be achieved by compensating for leaf loss in terms of growth rate, which entails either allocating more new assimilates to leaves, allocating new assimilates more efficiently to leaf area (i.e. by increasing specific leaf area), or growing faster with existing leaf area (i.e. by increasing net assimilation rate). Genetic variation in tolerance and compensatory responses would allow populations to adapt to changes in disturbance events that entail leaf loss.

Individual heterogeneity could also have implications for management. Plant and animal populations are managed at many different levels ranging from harvest from natural populations to modern agricultural practices. When harvesting from natural populations, it might be beneficial to spare the individuals that are most important for future production. Individuals could be spared, either because they contribute most to population growth, because they are tolerant to harvesting (which is relevant when only part of a plant is harvested), or when they start producing less or lower quality product. The productivity of natural populations could also be increased by actively promoting those environmental conditions and genotypes that allow for high productivity, which is the basis of agriculture and common practice in forest management. To determine how this can best be done, knowledge of the causes of individual heterogeneity is necessary.

The general aim of this thesis is to identify and quantify the mechanisms that determine individual heterogeneity and to determine how this heterogeneity, in turn, affects population level processes. This aim was divided into four main questions that I addressed: (1) To what extent do individuals differ in performance? (2) What causes individual heterogeneity in performance? (3) What are the demographic consequences of individual heterogeneity? (4) Can individual differences be used to improve the management of populations? To answer these questions, we used the tropical forest understorey palm Chamaedorea elegans as a study system, of which the leaves are an important non-timber forest product that is being used in the floral industry worldwide. We collected demographic data, measured spatial variation in environmental conditions, and applied a defoliation treatment to simulate leaf harvesting, in a natural population in Chiapas, Mexico. Furthermore, we grew seedlings from different mothers from our study population in the greenhouses of Wageningen University, where we also applied a defoliation treatment.

In Chapter 2 we quantified the extent to which individuals differ in long-term growth rate, and analyzed the importance of fast growers for population growth. We reconstructed growth histories from internodes and showed that growth differences between individuals are very large and persistent in our study population. This led to large variation in life growth trajectories, with individuals of the same age varying strongly in size. This shows that not only in canopy trees but also in species in the light limited understorey growth differences can be very large. Past growth rate was found to be a very good predictor of current performance (i.e. growth and reproduction). Using an Integral Projection Model (i.e. a type of demographic model) that was based on size and past growth rate, we showed that fast-growing individuals are much more important for population growth than others: the 50% fastest growing individuals contributed almost two times as much to population growth as the 50% slowest growing individuals.

In Chapter 3 we analyzed the extent to which observed long-term growth differences can be caused by environmental heterogeneity. Short-term variation in performance was mainly driven by light availability, while soil variables and leaf damage had smaller effects, and spatial heterogeneity in light availability and soil pH were autocorrelated over time. Using individual-based simulation models, we analyzed the extent to which spatial environmental heterogeneity could explain observed long-term variation in growth, and showed that this could largely be explained if the temporal persistence of light availability and soil pH was taken into account. We also estimated long-term inter-individual variation in reproduction to be very large. We further analyzed the importance of temporal persistence in environmental variation for long-term performance differences, by analyzing the whole range of values of environmental persistence, and the strength of the effect of the environmental heterogeneity on short-term performance. We showed that long-term performance differences become large when either the strength of the effect of the environmental factor on short-term performance is large, or when the spatial variation in the environmental factor is persistent over time. This shows that an environmental factor that in a short-term study might have been dismissed as unimportant for long-term performance variation, might, in reality, contribute strongly.

In Chapter 4 we tested for genetic variation in growth potential, tolerance to leaf loss, compensatory growth responses, and if growth potential and tolerance were genetically correlated in our study population. We quantified compensatory responses with an iterative growth model that takes into account the timing of leaf loss. Genetic variation in growth potential was large, and plants compensated strongly for leaf loss, but genetic variation in tolerance and compensatory growth responses was very limited. Growth performances in defoliated and undefoliated conditions were positively genetically correlated (i.e. the same genotypes perform relatively well compared to others, both with and without the stress of leaf loss). The high genetic variation in growth potential and the positive correlation between treatments suggests that the existence of super-performing individuals in our study population likely has (at least in part) a genetic basis. These super-performing individuals, that grow fast even under the stress of leaf loss, possibly contribute disproportionately to population resistance and resilience to disturbance. The low genetic variation in tolerance and compensatory responses, however, suggests that populations might have limited ability to adapt to changes in disturbance regimes that entail increases in leaf loss. Furthermore, the high genetic variation in growth potential could potentially be used in management practices like enrichment planting.

In Chapter 5 we explore the potential of using individual heterogeneity to design smarter harvest schemes, by sparing individuals that contribute most to future productivity. We tested if fast and slow growers, and small and large individuals, responded differently to leaf loss in terms of vital rates, but found only very limited evidence for this. Using Integral Projection Models that were based on stem length and past growth rate, we simulated leaf harvest over a period of 20 years, in several scenarios of sparing individuals, which we compared to “Business as usual” (i.e. no individuals being spared, BAU). Sparing individuals that are most important for population growth, was beneficial for population size (and could, therefore, reduce extinction risk), increased annual leaf harvest at the end of the simulation period, but cumulated leaf harvest over 20 years was much lower compared to BAU. Sparing individuals that produced leaves of non-commercial size (i.e. <25cm), therefore allowing them to recover, also resulted in a lower total leaf harvest over 20 years. However, a much higher harvest (a three-fold increase) was found when only leaves of commercial size were considered. These results show that it is possible to increase yield quality and sustainability (in terms of population size) of harvesting practices, by making use of individual heterogeneity. The analytical and modeling methods that we present are applicable to any natural system from which either whole individuals, or parts of individuals, are harvested, and provide an extra tool that could be considered by managers and harvest practitioners to optimize harvest practices.

In conclusion, in this thesis, I showed that in a long-lived understorey palm growth differences are very large and persistent (Chapter 2) and that it is likely that long-term differences in reproduction are also very large (Chapter 3). I also showed that spatial heterogeneity in environmental conditions can to a large extent explain these differences and that when evaluating the environmental drivers of individual heterogeneity, it is important to take the persistence of spatial variation into account (Chapter 3). Individual heterogeneity also is partly genetically determined. I showed that genetic variation in growth potential to be large (Chapter 4), and that fast growers keep on growing fast under the stress of leaf loss (Chapters 4,5). Therefore it is likely that genetic variation contributes to long-term differences between individuals. Genetic variation for tolerance and compensatory responses was estimated to be low (Chapter 4), suggesting that the adaptive potential of our study population to changes in disturbance events that entail leaf loss might be low. I also showed that super-performing individuals are much more important for the growth of the population (Chapter 2) and that individuals that are important for future production could be used to improve the management of natural populations (Chapter 5).

This study provides improved insight into the extent of individual heterogeneity in a long-lived plant species and its environmental and genetic drivers, and clearly shows the importance of individual heterogeneity and its drivers for population processes and management practices. It also presents methods on how persistent performance differences between individuals can be incorporated into demographic tools, how these can be used to analyze individual contributions to population dynamics, to extrapolate short-term to long–term environmental effects, and to analyze smart harvesting scenarios that take differences between individuals into account. These results indicate that individual heterogeneity, underlying environmental and genetic drivers, and population processes are all related. Therefore, when evaluating the effect of environmental change on population processes, and in the design of management schemes, it is important to keep these relations in mind. The methodological tools that we presented provide a means of doing this.

This paper reports on temporal and spatial variability of local climate and outdoor human thermal comfort within the Rotterdam agglomeration. We analyse three years of meteorological observations (2010–2012) from a monitoring network. Focus is on the atmospheric urban heat island (UHI); the difference in air temperature between urban areas and rural surroundings. In addition, we calculate the Physiologically Equivalent Temperature (PET) which is a measure of thermal comfort. Subsequently, we determine the dependency of intra-urban variability in local climate and PET on urban land-use and geometric characteristics. During a large part of the year, UHI-intensities in densely built areas can be considerable, under calm and clear (cloudless) weather conditions. The highest maximum UHI-values are found in summer, with 95-percentile values ranging from 4.3 K to more than 8 K, depending on the location. In winter, UHI-intensities are generally lower. Intra-urban variability in maximum UHI-intensity is considerable, indicating that local features have an important influence. It is found to be significantly related to building, impervious and green surface fractions, respectively, as well as to mean building height. In summer, urban areas show a larger number of discomfort hours (PET > 23 °C) compared to the reference rural area. Our results indicate that this is mainly related to the much lower wind velocities in urban areas. Also intra-urban variability in thermal comfort during daytime appears to be mainly related to differences in wind velocity. After sunset, the UHI effect plays a more prominent role and hence thermal comfort is more related with urban characteristics.

Soil acidity is well known to affect the species composition of natural vegetation. The physiological adaptations of plants to soil acidity and related toxicity effects and nutrient deficiencies are, however, complex, manifold and hard to measure. Therefore, generally applicable quantifications of mechanistic plant responses to soil acidity are still not available. An alternative is the semi-quantitative and integrated response variable ‘indicator value for soil acidity’ (Rm). Although relationships between measured soil pH and Rm from various studies are usually strong, they often show systematic bias and still contain high residual variances. On the basis of a well-documented national dataset consisting of 91 vegetation plots and a dataset with detailed, within-plot, pH measurements taken at three periods during the growing season, it is shown that strong spatiotemporal variation of soil pH can be a critical source of systematic errors and statistical noise. The larger part of variation, however, could be explained by the moisture status of plots. For instance, Spearman's rho decreased from 93% for dry plots and 87% for moist plots to 59% for wet plots. The loss of relation between soil pH and Rm in the moderately acid to alkaline range at increasingly wetter plots is probably due to the establishment of aerenchyma-containing species, which are able to control their rhizosphere acidity. Adaptation to one site factor (oxygen deficit) apparently may induce indifference for other environmental factors (Fe2+, soil pH). For predictions of vegetation response to soil acidity, it is thus important to take the wetness of plots into account

In integrated small-scale aquaculture farming, animal and human excreta maybe used as fish feed and pond fertilizer, thereby enhancing transmission of fish-borne zoonotic trematodes (FZTs) from final hosts, like humans, pigs and chickens, to snails. Areas within a pond could vary in trematode egg-load due to the immediate bordering land, and this might provide implications for control of these trematodes or sampling in field studies measuring FZT prevalence in snails. We therefore estimated the effect of bordering land use on prevalence and FZT burden in snails in different areas within small-scale aquaculture ponds. Nine sampling areas within a pond were assigned in six ponds. For each sampling area, about 120 Melanoides tuberculata snails were collected. Based on land use bordering a sampling area, these were categorized in 5 risk-categories: low-risk (road, rice planted in pond, agriculture, or middle of pond), human access point to pond, livestock sty (pigs or poultry), both human access point and livestock sty, and water connection to canal. In total, 5392 snails were collected. Percentages of snails with parapleurolophocercous cercariae varied between 6% in areas categorized as low-risk and areas with livestock sty only to 15% in areas with both human access point and livestock sty; only this 15% was significantly different from the prevalence in the low-risk category. Percentages of snails with xiphidio cercariae did not differ between risk-categories and varied between 5% and 10%. Mean snail size was 15.2 mm, and was significantly associated with both the probability of infection as well as parasite burden. Very small differences in parasite burden were found at different land use areas; the maximum difference was about 11 cercariae. This study demonstrated only small differences between areas surrounding a pond on risk of snails to be infected with fish-borne trematodes within different pond areas. In field studies on FZTs in M. tuberculata snails in ponds, sampling from ponds can therefore be done without considering areas within ponds.

Soil erosion in southeast Spain is a complex process due to strong interactions between biophysical and human components. Significant progress has been achieved in the understanding of soil hydrological behavior, despite the fact that most investigations were focused on the experimental plot scale. Although experimental plots allow exploring the effect of multiple biophysical and anthropogenic factors, they provide limited insights in the combined effect of all factors acting together at the landscape scale. In this study, area-specific sediment yields (SSY) have been estimated based on the volume of sediment trapped behind 36 check dams in the southeast of Spain. Low SSY-values were reported (mean = 1.40 t ha-1 year-1: median = 0.61 t ha-1 year-1). SSY variability could be explained for 67% by catchment characteristics such as drainage area, soil characteristics, land cover, average catchment slope, and annual rainfall. The low SSY values are probably caused by the agricultural abandonment that occurred over the past decades and allowed the recovery of natural vegetation. Furthermore, our results suggest that the soils have eroded in the past to such an extent that nowadays not much sediment is detached by overland flow due to residual enrichment of clay and stones. Also, sediment is to a large extent trapped locally in the catchment, as indicated by the negative relationship between SSY and catchment area

Agricultural intensification has led to a loss of biological diversity at various spatial and temporal scales and understanding the mechanisms driving these changes would help target conservation efforts accordingly. In this study we used additive partitioning of diversity and the Jaccard index of similarity to estimate the spatial and temporal patterns of plant diversity on ditch banks under different management regimes (nature reserves and agricultural areas). We focused on a total of 118 species, including 18 indicator species of conservation interest, at 42 sites in three successive sampling periods. For all species taken together, beta diversity contributed most to total observed species diversity, but was less than expected under random distribution. Indicator species showed greater beta diversity on a spatial scale compared to all species, but much less so on a temporal scale. Importantly, the differences in indicator species composition on a spatial scale are probably due to environmental heterogeneity and dispersal limitation, indicating that management strategies should focus on both factors. Nature reserves showed higher alpha diversity within sites because of possible lower nutrient inputs and grazing intensity compared with agricultural areas, while both exhibited scale-dependent dispersal limitation.

Tropical rainforest areas are difficult to classify in the digital analysis of remote sensing data because of spatial heterogeneity. Often many technical solutions are adopted to reduce the ‘problem’ of spatial heterogeneity. This thesis describes theory and methods that now use this heterogeneity during the digital image classification. With spatial heterogeneity, spatial aggregation levels such as patches,patch-mosaics and landscapes can be distinguished. Consequently, vegetation patterns can be related to functional management units at different decision-levels. The developed theory and methods thus save two birds with one stone: (a) the classification is completely digitally, and (b) the classification provides information on deforestation that meets the needs of decision-makers. This thesis further recommends approaching all land cover classifications from a heterogeneous perspective for understanding and controlling environmental processes on a global level. This can enhance a sustainable development of tropical rainforest areas for the benefit of future generations.

Fluxes of methane (CH4) and carbon dioxide (CO2) estimated by empirical models based on small-scale chamber measurements were compared to large-scale eddy covariance (EC) measurements for CH4 and to a combination of EC measurements and EC-based models for CO2. The experimental area was a flat peat meadow in the Netherlands with heterogeneous source strengths for both greenhouse gases. Two scenarios were used to assess the importance of stratifying the landscape into landscape elements before up-scaling the fluxes measured by chambers to landscape scale: one took the main landscape elements into account (field, ditch edge ditch), the other took only the field into account. Non-linear regression models were used to up-scale the chamber measurements to field emission estimates. EC CO2 respiration consisted of measured night time EC fluxes and modeled day time fluxes using the Arrhenius model. EC CH4 flux estimate was based on daily averages and the remaining data gaps were filled by linear interpolation. The EC and chamber-based estimates agreed well when the three landscape elements were taken into account with 16.5% and 13.0% difference for CO2 respiration and CH4, respectively. However, both methods differed 31.0% and 55.1% for CO2 respiration and CH4 when only field emissions were taken into account when up-scaling chamber measurements to landscape scale. This emphasizes the importance of stratifying the landscape into landscape elements. The conclusion is that small-scale chamber measurements can be used to estimate fluxes of CO2 and CH4 at landscape scale if fluxes are scaled by different landscape elements

Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO2 based on 163 site-years of eddy covariance data, from 39 northern-hemisphere research sites located at latitudes ranging from ~29°N to ~64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE in deciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands.

Approximately 42% of the Dutch agricultural land is drained using tile drains. Of all Dutch soil types peat soils are responsible for the highest emission of nitrous oxide per unit of surface for agricultural land. The emission of nitrous oxide is characterized by its high spatial variability, to which the presence of tile drains may contribute. The objective of this study was to quantify the spatial variability due to drainage of peat soil on grassland

It is widely believed that the neutral theory of biodiversity cannot be used for parameter inference if the assumption of neutrality is not met. The goal of this work is to extend this neutral framework to quantify the intensity of recruitment limitation (limited dispersal plus environmental filtering) in natural species assemblages. We model several local communities as part of a larger metacommunity, and we assume that neutrality holds in each local community, but not in the metacommunity. The immigration rate m does not only reflect dispersal limitation into a given local community, but also the intensity of environmental filtering. We develop a novel statistical method to infer the immigration parameter m in each local community. Using simulated datasets, we show that m indeed depends on both dispersal limitation and on the intensity of environmental filtering. We then apply this method to a network of tropical tree plots in central Panama. Inferred recruitment rates m were positively correlated with the fraction of trees dispersed by mammals, and with annual rainfall, possibly due to a weaker environmental filtering as rainfall increases. Finally, m, as estimated from trees greater than 1 cm trunk diameter, were significantly larger than an estimation based on trees greater than 10 cm trunk diameter. This suggests a cumulative effect of environmental filtering upon trees throughout their ontogeny.

Loss of biodiversity, including agro-biodiversity affects smallholders in dry-land regions by decreasing the buffering capacity of the agro-ecosystem and increasing proneness to yield variability including crop failure due to weather extremes. Loss of biodiversity is associated with land use/land cover (LULC) changes that are related to a range of biophysical and socio-economic drivers. This thesis is focused on the Tigray region in northern Ethiopia which has experienced severe loss of biodiversity over the last decades at the regional scale, while loss of genetic variation of crops at the farm and field scale are ongoing as a result of agricultural technology adoption processes. The overall goal of this thesis research was to identify and analyse factors affecting loss of agro-biodiversity in Tigray, Ethiopia, and relate agro-biodiversity loss to LULC changes, soil erosion, farming practices and agricultural productivity. A multi-scale approach was adopted. At the regional scale, LULC changes over the last decades were investigated using a time-series of remotely sensed data to assess changes in biodiversity. At the farm scale, changes in farming practices and land use between 2000 and 2005 were described along with their effects on agro-biodiversity. These changes were related to biophysical and socio-economic drivers. Finally, at the field scale, the consequences of the presence of Acacia albida trees for productivity were assessed. A survey among 151 farms in Tigray indicated that higher numbers of species of trees and shrubs, along with cultivation of land races was associated with traditional farming practices of smallholders in 2000 and 2005. Classified maps from remotely sensed data indicated that significant changes in LULC were accompanied by loss of biodiversity and intensification of agricultural production. At the same time, overall caloric yields were highest and soil erosion lowest in sparsely cultivated areas with high biodiversity, where traditional farming practices still dominate. At the farm scale, it was shown that A. albida trees contribute significantly to soil fertility and barley yield. Results of this project may assist policy development on agro-biodiversity restoration by providing information on long-term historical trends, insight into their drivers, and consequences for food security among resource poor smallholders in the region.